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_base_ = [
'/home/liuziyuan/proj/rmcd-kd/configs/_base_/models/KD-lightcdnet.py',
'/home/liuziyuan/proj/rmcd-kd/configs/common/standard_512x512_200k_cgwx.py']
dataset_type = 'LEVIR_CD_Dataset'
data_root = '/nas/datasets/lzy/RS-ChangeDetection/CGWX'
crop_size = (512, 512)
checkpoint_student = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/initial/best_mIoU_iter_195000.pth'
checkpoint_teacher_l = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/large/best_mIoU_iter_185000.pth'
checkpoint_teacher_m = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/medium/best_mIoU_iter_199000.pth'
checkpoint_teacher_s = '/nas/datasets/lzy/RS-ChangeDetection/checkpoints_distill/LightCDNet/teacher_ckpt/small/best_mIoU_iter_193000.pth'
model = dict(
# student
init_cfg=dict(type='Pretrained', checkpoint=checkpoint_student),
# teacher large
init_cfg_t_l = dict(type='Pretrained', checkpoint=checkpoint_teacher_l),
# teacher medium
init_cfg_t_m = dict(type='Pretrained', checkpoint=checkpoint_teacher_m),
# teacher small
init_cfg_t_s = dict(type='Pretrained', checkpoint=checkpoint_teacher_s),
decode_head=dict(
sampler=dict(type='mmseg.OHEMPixelSampler', thresh=0.7, min_kept=100000)))
# optimizer
optimizer = dict(
type='AdamW',
lr=0.003,
betas=(0.9, 0.999),
weight_decay=0.05)
optim_wrapper = dict(
_delete_=True,
type='OptimWrapper',
optimizer=optimizer)
param_scheduler = [
dict(
type='LinearLR', start_factor=1e-6, by_epoch=False, begin=0, end=1000),
dict(
type='PolyLR',
power=1.0,
begin=1000,
end=100000,
eta_min=0.0,
by_epoch=False,
)
]
# training schedule for 100k
train_cfg = dict(type='IterBasedTrainLoop', max_iters=100000, val_interval=1000)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=100, log_metric_by_epoch=False),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', by_epoch=False, interval=1000,
save_best='mIoU'),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(type='CDVisualizationHook', interval=1,
img_shape=(512, 512, 3)))